Whilst artificial intelligence (AI) is riding high on the hype cycle right now, it’s nothing new in financial services. It’s been used in the back end of forward-looking financial services firms for years, automating processes and informing fraud prevention strategies.
Generative (Gen) AI, such as ChatGPT and other large language models (LLMs), is driving much of the current excitement. It’s placed AI’s considerable power into the hands of consumers. They can see Gen AI generating text and graphics – and they’re keen to explore and find out how it can benefit them.
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Against this backdrop, embedded finance – enhanced by Gen AI – is bolstering the financial services sector by offering seamless customer experiences, cost savings, operational efficiency, and market competitiveness.
According to research from Markets and Markets, the global Gen AI market size will reach $136.7bn by 2030, growing at a compound annual growth rate (CAGR) of 36.7%. But as embedded finance providers seek to harness the undoubted potential of Gen AI, it’s crucial they remember to keep humans in the loop.
Unlocking new benefits
The cost-saving potential of integrating AI-powered solutions into embedded finance is multifaceted. For example, AI automates routine and repetitive tasks such as data entry, transaction processing, and document verification. This eliminates manual intervention, which saves time and labour costs.
By summarising transactional data to better inform credit decisions, Gen AI can also help to accelerate a lender’s end-to-end credit process. It can generate code to source and analyse credit data to gain a more accurate view into a customer’s risk profile and then generate default and loss probability estimates through models. And once a credit decision has been made, Gen AI can even draft the credit memo and contract.
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By GlobalDataBy wedding embedded finance with AI, brands can give their customers exactly what they want: interactions with loans, accounts, and payments that mirror the highly personal and frictionless experiences they enjoy elsewhere online.
One area where Gen AI is now particularly shifting the dial is customer service. Gen AI-powered chatbots can offer embedded finance providers a more agile and efficient route to improving customer service levels. The insight gained through these tools enables them to anticipate customer expectations and offer them what they want at the right time as part of an integrated, personalised omnichannel experience – enhancing customer engagement, satisfaction, and loyalty.
Considered collaboration between man and machine
However, even as Gen AI strategies become increasingly sophisticated, human oversight remains crucial.
The most responsible way for embedded finance providers to leverage Gen AI is to ensure that human review is carefully baked in. There are ethical concerns, and sometimes inherent bias in the models, that require sensible navigation. This can help to mitigate against unintended or damaging consequences.
For a start, even the most advanced LLMs are prone to ‘hallucinations’, where they perceive patterns or objects that are non-existent, creating nonsensical or inaccurate outputs. This makes them difficult to rely on as a sole, definitive source of truth, especially in the heavily regulated financial services arena.
And talking of regulation, the newly introduced European Union (EU) AI Act creates provisions to tackle the risks posed by Gen AI tools that are being harnessed by embedded finance providers to reimagine customer support by speeding up response times, handling routine enquiries, and enhancing overall customer satisfaction levels.
These provisions will require the producers of the underlying AI systems to become more transparent about the material used to train their models, so they comply fully with EU copyright law. They will also require embedded finance providers to keep a human finger on the pulse to ensure they are fully complying with the new regulation. The EU AI Act is the world’s first comprehensive framework for constraining the risks of AI, and such an approach could be copied by other jurisdictions, meaning that compliance officers around the world should play a central role in rolling out Gen AI applications.
True success lies in finding the right balance between man and machine. Gen AI should be seen as a co-pilot, and not the pilot. It should augment knowledge workers rather than replace them – and this is the case whether its helping a developer to write code, a marketer to write copy, or a customer success team to improve the user experience. Human oversight is crucial in ensuring accuracy and adherence to ethical behaviours.
Embedded finance providers must therefore retain the human touch when it comes to integrating Gen AI. For example, if an LLM generated the answers to a new set of FAQs, they will still need to be carefully reviewed and edited by a real person. A thorough human review of the data gathered by Gen AI tools can also enable brands to then offer the right recommendations that are tailored to a user’s specific circumstances and goals as they seek to emerge from the worst of the cost-of-living crisis.
By blending AI innovation with human judgement, brands can help to create a more resilient and responsive financial services sector that meets the fast-evolving needs of consumers.
Nima Montazeri is Chief Product Officer, Liberis
